1. Field
This application relates generally to human-computer interaction, and more
particularly to a system and method of user authentication using bioresponse data.
2. Related Art
Eye-tracking data and/or other bioresponse data can be collected from a variety of
devices and sensors that are becoming more and more prevalent today. Laptops frequently include microphones and high-resolution cameras capable of monitoring a person's facial expressions, eye movements, or verbal responses while viewing or experiencing media. Cellular telephones now include high-resolution cameras, proximity sensors, accelerometers, touch-sensitive screens in addition to microphones and buttons, and these “smartphones” have the capacity to expand the hardware to include additional sensors. Moreover, high-resolution cameras are decreasing in cost making them prolific in a variety of applications ranging from user devices like laptops and cell phones to interactive advertisements in shopping malls that respond to mail patrons' proximity and facial expressions. The capacity to collect eye-tracking data and other bioresponse data from people interacting with digital devices is thus increasing dramatically.
At the same time, many website administrators try to prevent unwanted internet
bots from accessing websites. Various types of challenge-response tests are used to ensure that the response is generated by a person and not an internet hot. The process can involve a computer asking a user to complete a simple test which the computer is able to grade. The test can be designed to be easy for a computer to generate, but difficult for a computer to solve; such that if a correct solution is received, it can be presumed to have been entered by a human. A common type of challenge-response is the CAPTCHA. A CAPTCHA can require a user to type letters or digits from a distorted image that appears on the screen. However, many internet bots have already been written that can solve various forms of CAPTCHA tests. Thus, a method and system are desired for using eye-tracking data in a challenge/response test to authenticate a human user.